| Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive explanations P Das, A Kashem Case Studies in Construction Materials 20, e02723, 2024 | 49 | 2024 |
| Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses A Kashem, R Karim, SC Malo, P Das, SD Datta, M Alharthai Case Studies in Construction Materials 20, e02991, 2024 | 48 | 2024 |
| Compressive strength prediction of high-strength concrete using hybrid machine learning approaches by incorporating SHAP analysis A Kashem, P Das Asian Journal of Civil Engineering 24 (8), 3243-3263, 2023 | 36 | 2023 |
| Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric analyses A Kashem, R Karim, P Das, SD Datta, M Alharthai Case Studies in Construction Materials 20, e03030, 2024 | 32 | 2024 |
| Prediction of high-performance concrete compressive strength using deep learning techniques N Islam, A Kashem, P Das, MN Ali, S Paul Asian Journal of Civil Engineering 25 (1), 327-341, 2024 | 23 | 2024 |
| Sustainable of rice husk ash concrete compressive strength prediction utilizing artificial intelligence techniques S Paul, P Das, A Kashem, N Islam Asian Journal of Civil Engineering 25 (2), 1349-1364, 2024 | 17 | 2024 |
| A comparative study of machine learning models for construction costs prediction with natural gradient boosting algorithm and SHAP analysis P Das, A Kashem, I Hasan, M Islam Asian Journal of Civil Engineering, 1-16, 2024 | 16 | 2024 |
| Prediction of compressive strength of high-performance concrete using optimization machine learning approaches with SHAP analysis MM Islam, P Das, MM Rahman, F Naz, A Kashem, MH Nishat, ... Journal of Building Pathology and Rehabilitation 9 (2), 1-20, 2024 | 6 | 2024 |
| A comparative study of ensemble machine learning models for compressive strength prediction in recycled aggregate concrete and parametric analysis P Das, A Kashem, JU Rahat, R Karim Multiscale and Multidisciplinary Modeling, Experiments and Design, 1-26, 2024 | 5 | 2024 |
| Alkali-activated binder concrete strength prediction using hybrid-deep learning along with shapely additive explanations and uncertainty analysis P Das, A Kashem, M Islam, A Ahmed, MA Haque, M Khan Construction and Building Materials 435, 136711, 2024 | 3 | 2024 |
| Comparative analysis of advanced deep learning models for predicting evapotranspiration based on meteorological data in bangladesh S Paul, SZ Farzana, S Das, P Das, A Kashem Environmental Science and Pollution Research 31 (50), 60041-60064, 2024 | 2 | 2024 |
| Hybrid deep learning models for multi-ahead river water level forecasting A Kashem, P Das, MM Hasan, R Karim, NM Nasher Earth Science Informatics, 1-17, 2024 | 2 | 2024 |
| Metaheuristic-based machine learning approaches of compressive strength forecasting of steel fiber reinforced concrete with SHapley Additive exPlanations A Kashem, A Anzer, R Jagirdar, MS Sojib, F Farooq, P Das Multiscale and Multidisciplinary Modeling, Experiments and Design 8 (1), 61, 2025 | 1 | 2025 |
| Prediction of mechanical properties of eco-friendly concrete using machine learning algorithms and partial dependence plot analysis T Roy, P Das, R Jagirdar, M Shhabat, MS Abdullah, A Kashem, ... Smart Construction and Sustainable Cities 3 (1), 2, 2025 | | 2025 |
| Deep learning approaches for short-crop reference evapotranspiration estimation: a case study in Southeastern Australia U Baishnab, MS Hossen Sajib, A Islam, S Akter, A Hasan, T Roy, P Das Earth Science Informatics 18 (1), 1-17, 2025 | | 2025 |
| Water proofing performance assessment of hydrophobic agent-based Portland cement concrete: A multi-dimensional experiment approach P Das, MA Haque, M Islam, A Chakraborty Journal of Building Engineering 96, 110600, 2024 | | 2024 |
| Deep Learning Models for Reference Evapotranspiration Prediction in Bangladesh A Kashem, P Das, U Baishnab MDPI, 2024 | | 2024 |
Abul KashemBachelor of Science in Civil Engineering, Leading University, BangladeshVerified email at lus.ac.bd